A quality measure for compressed image sequences based on an eye-movement compensated spatio-temporal model

We propose a vision model for predicting the perceptibility of coding errors in digital image sequences. Eye movements have a significant effect on distortion visibility, and hence they form an important part of the model. A modified motion estimator is used to predict the eye movements of a viewer when watching an image sequence. The spatio-temporal frequency sensitivity and masking effects are included in the model. The model is based on a decomposition of the signal into frequency and orientation bands to allow accurate modeling of spatial masking by a contrast transducer. We describe how the proposed quality measure can be used to compress image sequences using a constrained MPEG-2 encoder